144 lines
4.8 KiB
Python
144 lines
4.8 KiB
Python
#!/usr/bin/env python
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# Copyright (c) 2016 Hewlett Packard Enterprise Development Company, L.P.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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import logging
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import random
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import voluptuous
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import monasca_analytics.banana.typeck.type_util as type_util
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import monasca_analytics.component.params as params
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import six
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import monasca_analytics.source.markov_chain.base as base
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import monasca_analytics.source.markov_chain.events as ev
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import monasca_analytics.source.markov_chain.prob_checks as pck
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import monasca_analytics.source.markov_chain.state_check as dck
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import monasca_analytics.source.markov_chain.transition as tr
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import monasca_analytics.util.timestamp as tp
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from monasca_analytics.util import validation_utils as vu
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logger = logging.getLogger(__name__)
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class MonascaMarkovChainSource(base.MarkovChainSource):
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@staticmethod
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def validate_config(_config):
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markov_schema = voluptuous.Schema({
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"module": voluptuous.And(six.string_types[0],
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vu.NoSpaceCharacter()),
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"sleep": voluptuous.And(
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float, voluptuous.Range(
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min=0, max=1, min_included=False, max_included=False)),
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}, required=True)
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return markov_schema(_config)
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@staticmethod
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def get_default_config():
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return {
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"module": MonascaMarkovChainSource.__name__,
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"sleep": 0.01,
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}
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@staticmethod
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def get_params():
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return [
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params.ParamDescriptor('sleep', type_util.Number(), 0.01)
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]
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def get_feature_list(self):
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return ["vm1", "vm2", "host1", "host2"]
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def _create_system(self):
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mc = tr.MarkovChain([])
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vm_triggers = [
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ev.Trigger(
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event_builder=MonascaFakeMetricBuilder("vm.mem.used_mb"),
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node_check=dck.TrueCheck(),
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prob_check=pck.NoProbCheck()
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),
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ev.Trigger(
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event_builder=MonascaFakeMetricBuilder("cpu.idle_perc"),
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node_check=dck.TrueCheck(),
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prob_check=pck.NoProbCheck()
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),
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ev.Trigger(
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event_builder=MonascaFakeMetricBuilder(
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"cpu.total_logical_cores"),
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node_check=dck.TrueCheck(),
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prob_check=pck.NoProbCheck()
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)
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]
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host_trigger = ev.Trigger(
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event_builder=MonascaFakeMetricBuilder("mem.total_mb"),
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node_check=dck.TrueCheck(),
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prob_check=pck.NoProbCheck()
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)
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return [
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# vm.mem.used_mb
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base.StateNode(3, mc, vm_triggers[0], _id="vm1"),
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base.StateNode(1, mc, vm_triggers[0], _id="vm2"),
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# cpu.idle_perc
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base.StateNode(0.75, mc, vm_triggers[1], _id="vm1"),
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base.StateNode(0.75, mc, vm_triggers[1], _id="vm2"),
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# cpu.total_logical_cores
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base.StateNode(3, mc, vm_triggers[2], _id="vm1"),
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base.StateNode(2, mc, vm_triggers[2], _id="vm2"),
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# mem.total_mb
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base.StateNode(5, mc, host_trigger, _id="host1"),
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base.StateNode(6, mc, host_trigger, _id="host2"),
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]
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class MonascaFakeMetricBuilder(object):
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def __init__(self, metric_name):
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"""
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:type metric_name: str
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:param metric_name: The name of the metric
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"""
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self.metric_name = metric_name
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def __call__(self, node, fake_date, request):
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"""
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:type node: monasca_analytics.source.markov_chain.base.StateNode
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:param node: The node associated with the event.
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:type fake_date: datetime.datetime
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:param fake_date: A date that you can use to generate a ctime.
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:type request:
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monasca_analytics.source.markov_chain.base.RequestBuilder
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"""
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half_hour = 60 * 60 / 2
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request.send({
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"metric": {
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"name": self.metric_name,
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"dimensions": {
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"service": "monitoring",
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"hostname": node.id()
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},
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"timestamp": tp.timestamp(fake_date) +
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random.randint(- half_hour, half_hour),
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"value": node.state
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},
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"meta": {
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"tenantId": 0,
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"region": "earth"
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},
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"creation_time": 0
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})
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